Informações sobre o curso: This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help learners be trained to be a competent data scientists. Empowered by bringing lecture notes together with lab sessions based on the y-TextMiner toolkit developed for the class, learners will be able to develop interesting text mining applications.

Desenvolvido por: Yonsei University

Ministrado por: Min Song, Professor
Library & Information Technology

Nível	Intermediário
Idioma	Inglês, Legendas: Espanhol, Chinês (simplificado)
Como ser aprovado	Seja aprovado em todas as tarefas para concluir o curso.
Classificação do usuário	4.1 estrelas Classificação média do usuário 4.1Veja o que os aprendizes disseram

Programa

SEMANA 1

Course Logistics and the Text Mining Tool for the Course

4 videos, 1 leituras

Vídeo: 1.2 Explanations of the y-TextMiner package and the datasets
Vídeo: 1.3 How-to-do: workspace installation and setup
Vídeo: 1.4 How-to-use: the y-TextMiner package (download it at http://informatics.yonsei.ac.kr/yTextMiner/yTextMiner1.2.zip)
Reading: What is Text Mining?
同学互评: y-TextMiner installation and a simple Java program

SEMANA 2

Text Preprocessing

5 videos, 1 leituras

Vídeo: 2.2 What is text mining?
Vídeo: 2.3 Description of preprocessing techniques
Vídeo: 2.4 How-to-do: normalization including tokenization and lemmatization
Vídeo: 2.5 How-to-do: N-Grams
Reading: Text Preprocessing
同学互评: Preprocessing Practice

SEMANA 3

Text Analysis Techniques

6 videos, 2 leituras

Vídeo: 3.2 Explanations of named entity recognition
Vídeo: 3.3 Explanations of dependency parsing
Vídeo: 3.4 How-to-do: stopword removal and stemming
Vídeo: 3.5 How-to-do: NER and POS Tagging
Vídeo: 3.6 How-to-do: constituency and dependency parsing
Reading: Stemming and Lemmatization
Reading: Named Entity Recognition

Nota atribuída: Text Analysis Practice

SEMANA 4

Term Weighting and Document Classification

5 videos, 2 leituras

Vídeo: 4.2 Explanations of document classification
Vídeo: 4.3 Explanations of sentiment analysis
Vídeo: 4.4 How-to-do: computation of tf*idf weighting
Vídeo: 4.5 How-to-do: classification with Logistic Regression
Reading: Text Classification
Reading: TF-IDF

Nota atribuída: Document Classification Practice

SEMANA 5

Sentiment Analysis

6 videos, 1 leituras

Vídeo: 5.2 Explanations of sentiment analysis with unsupervised learning
Vídeo: 5.3 Explanations of sentiment analysis with CoreNLP, LingPipe and SentiWordNet
Vídeo: 5.4 How-to-do: sentiment analysis with CoreNLP
Vídeo: 5.5 How-to-do: sentiment analysis with LingPipe
Vídeo: 5.6 How-to-do: sentiment analysis with SentiWordNet
Reading: Opinion mining and sentiment analysis by Bo Pang and Lillian Lee

Nota atribuída: Sentiment Analysis Practice

SEMANA 6

Topic Modeling

5 videos, 1 leituras

Vídeo: 6.2 Explanations of LDA and DMR
Vídeo: 6.3 Description of Topic Modeling with Mallet
Vídeo: 6.4 How-to-do: LDA
Vídeo: 6.5 How-to-do: DMR
Reading: Introduction to Probabilistic Topic Models by David Blei

Nota atribuída: Topic Modeling Practice

Perguntas frequentes

Quando terei acesso aos vídeos do curso e às tarefas?

E se eu precisar de tempo adicional para concluir o curso?

O que obtenho se eu pagar por este curso?

Posso fazer este curso gratuitamente?

Como funciona a política de reembolso?Como funciona a política de reembolso?

Existe algum auxílio financeiro disponível?

Como funciona

课程作业

每门课程都像是一本互动的教科书，具有预先录制的视频、测验和项目。

来自同学的帮助

与其他成千上万的学生相联系，对想法进行辩论，讨论课程材料，并寻求帮助来掌握概念。

证书

获得正式认证的作业，并与朋友、同事和雇主分享您的成功。

Desenvolvedores

Yonsei University

Yonsei University was established in 1885 and is the oldest private university in Korea. Yonsei’s main campus is situated minutes away from the economic, political, and cultural centers of Seoul’s metropolitan downtown. Yonsei has 3,500 eminent faculty members who are conducting cutting-edge research across all academic disciplines. There are 18 graduate schools, 22 colleges and 133 subsidiary institutions hosting a selective pool of students from around the world. Yonsei is proud of its history and reputation as a leading institution of higher education and research in Asia.

Classificações e avaliações

Avaliado em 4.1 de 5 decorrente de 36 avaliações